Password resets, order status, invoice queries, appointment confirmations: most calls reaching a tier 1 technical support desk are repetitive and follow a known pattern, yet they still tie up human agents and generate hold times. According to Gartner (31 August 2022), conversational AI will cut contact centre agent labour costs by a cumulative $80 billion through 2026, automating one in ten agent interactions versus the 1.6% automated at the time of the prediction. A voice agent connected to your knowledge base resolves those tier 1 issues with no queue, and hands the call to a person, with the context already gathered, whenever the case requires it.
Tier 1 technical support is, by definition, the filter for the simplest and most frequent issues: the ones with a known answer in the knowledge base or ticket history, yet they still occupy a human agent's time and put the caller on hold. An AI voice agent changes that equation: it answers the call instantly, understands the real intent behind the request, and looks up the answer in the company's internal documentation instead of improvising. The goal is not to replace the support team, but to free it from the most repetitive part of the job so it can focus on the tier 2 and tier 3 issues that genuinely require human judgement.
At Summum IA we build this agent on the same RAG (Retrieval-Augmented Generation) engine documented in detail in our RAG and internal search service: the agent consults manuals, FAQs, warranty policies and past ticket resolutions before answering, so every reply is grounded in a real company document rather than a model hallucination. On top of that engine we define an explicit escalation blueprint — which queries the agent resolves on its own, which require identity verification first, and which are always transferred to a person — so the caller never gets stuck in an automated loop with no way out. The same use case exists on the text channel in our customer-support chatbot; the difference is the channel: voice for callers, text for those who prefer to type, both backed by the same knowledge base.
As of 2 August 2026, the EU AI Act (Regulation (EU) 2024/1689) requires, under Article 50, that any AI system interacting directly with people clearly disclose that it is an automated system, unless this is obvious from the context, and that any AI-generated audio be marked as such in a machine-readable format. A technical-support voice agent falls squarely within that scope: it interacts by phone with real customers who must know, from the first second of the call, that they are talking to an AI system. Summum IA delivers every agent already prepared for that obligation, with the call-opening disclosure and the audit trail needed for the compliance file.
We analyse call and support-ticket history to identify which tier 1 issues account for the highest volume — access, order status, billing, appointments — and which existing documentation can resolve them without human intervention.
We connect the agent to your knowledge base (manuals, FAQs, policies, ticket-resolution history) via RAG, so every answer rests on a real company document rather than a generic model response.
We document, in a blueprint, which queries the agent handles alone, which require identity verification, and which are always handed to a person — together with the context summary the human agent receives when taking over the call.
We put the agent into production with a monitoring panel for autonomous resolution rate, escalation reasons and average call duration. We review performance monthly and expand the knowledge base with the real issues we detect.
The operational detail: what we deliver as part of the work and what we keep alive afterwards.
Tier 1 support blueprint
Documented diagram of the issues the agent resolves, those that require identity verification, and the exact conditions for escalating to a person.
RAG response engine
Connection of the agent to the company's knowledge base (FAQs, manuals, ticket history) so every answer is grounded in real documentation.
Telephony and helpdesk integration
SIP/VoIP connector or API to your cloud phone system, plus integration with the ticketing system or CRM already used for support.
AI Act Article 50 compliance
AI disclosure at the start of the call, technical marking of the generated audio, and audit trail for the regulatory file under Regulation (EU) 2024/1689.
Autonomous resolution rate dashboard
Dashboard showing the share of calls resolved without human intervention, the most frequent escalation reasons, and average duration, as the service's sales metric.
Monthly retraining
Periodic review of real calls to expand the agent's knowledge base and progressively reduce avoidable escalations.
The tier 1 support voice agent relies on the group's RAG engine and shares its use case with the customer-support chatbot on the text channel; the three are combined by the channel the customer arrives through, without duplicating keyword or content between them.
The RAG engine the agent is built on: it connects the voice response to the company's real documentation instead of generic model answers.
View service → iaThe same tier 1 support use case on the text channel, for customers who prefer to type rather than call; it shares the same knowledge base as the voice agent.
View service →Yes. Article 50 of Regulation (EU) 2024/1689 (the AI Act) requires AI systems that interact directly with people to disclose that they are automated, unless this is obvious from context, and requires generated audio to be marked as such. These obligations apply from 2 August 2026. Every agent we deploy includes the call-opening disclosure and the required audit trail.
Those with a clear answer in your knowledge base: password or access resets, order or shipment status, invoice amount or line-item queries, appointment confirmation or rescheduling. The exact scope is defined case by case during the mapping phase, not as a fixed list.
The agent detects when a query is beyond its scope or when the customer explicitly asks to speak to a person, and transfers the call with a summary of the context already gathered, so the human agent doesn't have to start from zero.
No. The goal is to absorb the volume of repetitive tier 1 issues so your team can spend its time on tier 2 and tier 3 cases that genuinely require technical judgement, not to eliminate the human role.
Yes, it integrates via API with the usual helpdesk and CRM platforms, logging each call as a ticket or updating an existing one, so the support history stays unified regardless of channel.
With a dashboard tracking autonomous resolution rate (share of calls closed without escalation), the most frequent escalation reasons, and average call duration. That's the metric reviewed every month to decide what to add to the knowledge base.